https://academicjobsonline.org/ajo/Cornell/EN-DEAN/POSTDOC
The newly established Cornell University Duffield Engineering Education Research Institute is seeking multiple highly motivated scholars to join us as Postdoctoral Associates in Engineering Education Research across multiple projects. This is a unique opportunity to help shape a new, nationally visible Institute at a leading research university.
The Institute and its core faculty advance theory-informed and practice-engaged research on how engineers learn, how engineering knowledge and identities are formed, how we assess and evaluate learning, and how educational systems can be designed and transformed to support meaningful and impactful learning experiences. A central focus of the Institute is translating research into sustained evidence-based practice across engineering classrooms, programs, and institutions. The postdoctoral associates will work on one or more Institute projects and/or PI-Specific projects. Below is information about each project. As you review the projects, please reach out to the specific faculty contacts for more information.
(1) IMPACT Portal
Researchers create many measurement instruments for studying teaching and learning, including surveys, rubrics, and other tools, but those tools often stay within the projects that produced them. The IMPACT Portal, an initiative of Cornell's David A. Duffield Engineering Education Research Institute, will make them easier for both instructors and researchers to find and use. An instructor could choose a measure that fits their course, use it to examine a classroom innovation, and draw on the results for local scholarship of teaching and learning. When participating institutions use shared measures and contribute data alongside information about their course contexts, those local efforts can also build a longitudinal national dataset that lets us examine trends and make more meaningful comparisons across courses and institutions.
In this role, you will help lay the groundwork for building the portal in close collaboration with Drs. Alexandra Werth and Allison Godwin. You'll work with instructors, students, researchers, and administrators to understand what they need from it. You will gather existing instruments and help develop systematic ways to evaluate and communicate their validity evidence so users can choose measures that fit their contexts. You'll also help design a flexible system that supports finding and implementing measures, interpreting results locally, and conducting studies across sites, all within a sustainable infrastructure.
Desired qualifications
• A PhD (or near completion) in engineering education, educational measurement, educational or social psychology, or a related field• Experience developing or evaluating measurement instruments, grounded in contemporary validity frameworks such as the Standards for Educational and Psychological Testing or argument-based approaches to validation• Psychometric analysis skills, including confirmatory factor analysis, item response theory, and measurement invariance testing in R, Mplus, or similar software• Qualitative interviewing experience, including cognitive interviews or think-alouds for gathering response process evidence• Qualitative data analysis experience (e.g., thematic analysis, qualitative coding)• Human subjects research experience, including writing IRB protocols and consent materials• Sound data management practices, including documentation, de-identification, version control, and secure storage• Clear written and verbal communication with both researchers and practitioners
(2) Postdoctoral Researcher in Quantum Education at MARQUIS
Traditional undergraduate research opportunities reach only a fraction of the students who could benefit from them. Access is especially limited in quantum information science, where specialized research facilities are often concentrated at large, research-intensive institutions. MARQUIS, a National Science Foundation Quantum Leap Challenge Institute, is developing a Quantum Course-based Undergraduate Research Experience (QCURE) to broaden access to authentic research in quantum engineering. Students will use real fabrication and characterization datasets available through Q-VAULT to develop hypotheses, interpret evidence, and practice reproducible research.
In this role, you will work closely with Dr. Alexandra Werth and the MARQUIS research team to develop and study the QCURE. You will help select datasets and research questions appropriate for students, translate technical research into learning activities, and develop instructional materials and assessments. You will also design, pilot, and analyze surveys and support assessment of MARQUIS’s broader education, training, and workforce development (ETWD) initiatives. This work will include identifying program goals, gathering evidence about participants’ experiences and learning, and using findings to improve programs and contribute to education research.
We particularly welcome candidates with technical backgrounds who are interested in moving into education research, as well as candidates trained in engineering education or related fields who want to work in quantum education.
Desired qualifications
• A PhD (or near completion) in a relevant STEM field, engineering education, science education, or a related field.• Technical expertise in quantum information science, semiconductor research, materials science, applied physics, or engineering physics is particularly desirable.• Experience teaching, mentoring, or developing learning activities, with an interest in authentic research experiences and undergraduate STEM education.• Experience with survey design, educational assessment, or program evaluation, or a strong interest in developing these skills.• Quantitative data analysis skills in Python, R, MATLAB, or similar software, including clear documentation and reproducible workflows.• Experience with qualitative methods, such as interviews or analysis of student work, is welcome.• Ability to collaborate with technical researchers and explain complex ideas to students with different levels of preparation.• Clear written and verbal communication, careful data management, and willingness to develop expertise in human subjects research.
(3) Postdoctoral Researcher in AI Integration in Engineering Education
Generative AI is changing how engineers code, model, analyze data, and communicate technical work. Cornell Duffield Engineering is supporting a two-year experiment in which faculty reconsider what students need to learn and how they should learn it with, around, and sometimes without AI. Selected faculty will implement and study changes in their own courses or learning experiences, working with colleagues who are addressing related challenges. The initiative centers students’ critical thinking and engineering judgment while creating room to try new approaches to teaching and assessment.
In this two-year postdoctoral role, you will serve as an embedded education researcher and facilitator for a faculty working group. You will help participants turn their teaching ideas into researchable questions, design feasible assessments, and coordinate data collection within their courses. You will facilitate regular discussions, help faculty interpret evidence and refine their approaches, and analyze findings across projects. Each instructor will retain ownership of their course design; you will help the group make meaningful comparisons across different disciplinary contexts. You will also work with college and university staff and collaborate with faculty on publications, presentations, and practical resources for other instructors.
Desired qualifications
• A PhD (or near completion) in engineering education, another discipline-based education research field, learning sciences, higher education, or a related field• Experience designing and conducting research on teaching and learning in undergraduate STEM settings• Experience with qualitative and quantitative methods and the ability to choose methods appropriate to a question and course context• Experience developing assessments of student learning, particularly reasoning, critical thinking, or engineering judgment• Experience facilitating groups or collaborating with faculty on teaching, curriculum development, or educational research• Familiarity with generative AI tools and an interest in examining how their use changes disciplinary work and learning• Ability to coordinate several course-based projects, including timelines, data collection, IRB materials, and documentation• Clear communication with researchers and instructors, including translating findings into useful teaching guidance
(4) Postdoctoral Researcher in AI and Critical Thinking
An NSF-funded project led by Drs. Alexandra Werth, Natasha Holmes, and Michelle Smith at Cornell investigates whether generative AI can support student reflection and the development of critical thinking across physics, biology, and engineering courses. The project centers on the Automated Critical Thinking Reflection (ACTR) tool, which uses generative AI to tailor reflection prompts to students and their course experiences. By studying students’ reflections alongside measures of critical thinking, the team will examine how the design and personalization of prompts affect reflection quality and whether those differences relate to students’ critical thinking.
In this role, you will help design and conduct studies of AI-supported reflection, working closely with the research team and participating instructors. You will contribute to the development and evaluation of ACTR, including prompt design, connections between Qualtrics and AI systems, and reproducible workflows for processing and analyzing student responses. You will coordinate survey distribution and data collection, link reflection responses with other assessment data, and conduct qualitative and quantitative analyses. You will also help evaluate AI-assisted coding against human judgments and examine the accuracy and consistency of these methods. The role includes collaborating on publications and developing resources that help instructors and researchers use and study the tools at other institutions.
Desired qualifications
• A PhD (or near completion) in a STEM discipline, engineering or science education, learning sciences, educational psychology, or a related field• Experience with both qualitative and quantitative research methods, including analysis of written responses and statistical analysis of educational data• Strong programming and data analysis skills in Python, R, or similar languages, including building and documenting reproducible analysis workflows• Experience working with generative AI or large language models, including API integration, prompt design, and systematic evaluation of model outputs• Experience developing, distributing, and analyzing surveys, preferably in Qualtrics, including managing repeated administrations and linking responses across measures• Experience developing or applying qualitative codebooks and evaluating agreement among human or AI-assisted coders• Interest in student reflection, critical thinking, and the ways educational technology shapes learning• Human subjects research experience and sound practices for de-identification, secure data storage, and version control• Ability to work across disciplines and communicate research findings clearly through publications, presentations, and instructor resources
ACROSS ALL POSITIONS
The postdoctoral experience will include structured mentorship from Institute faculty, opportunities to lead collaborative projects, contribute as first authors on publications, and develop a research trajectory aligned with their long-term career goals. This position is designed to support successful transitions into academia, industry, or the public sector.
The desired start date is March 2027. This is a one-year appointment, with the possibility of renewal based on performance.
Application Procedure:
1. A cover letter that describes which projects are of most interest and why, desired goals for the postdoc, alignment of the candidate’s expertise with position requirements, and anticipated start date. Please note which projects you want to be considered for within your cover letter.2. Candidate CV, including publication list and date of Ph.D. graduation, and listing the Ph.D. advisor’s name. If not yet graduated, please note the estimated date for graduation. Font size should be no smaller than 11pt.3. Names of 2-3 recommenders that may be contacted as a reference after initial screening.
Applications received by November 15th, 2026 will be given a priority review. Applications will be accepted until the position is filled.
Inquiries may be directed to the faculty leads for the individual projects:
Dr. Allison Godwin, afg64@cornell.eduDr. Alexandra Werth, amw438@cornell.eduDr. Alexandra Coso Strong, acs386@cornell.eduDr. Jessica Rush Leeker, jrl399@cornell.edu
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Pay Ranges:
The hiring rate of pay for the successful candidate will be determined considering the following criteria:
- Prior relevant work or industry experience.
- Education level to the extent education is relevant to the position.
- Academic Discipline (faculty pay ranges reflects 9-month annual salary unless otherwise noted)
- Unique applicable skills.
